Multi-factor Early Warning Method for Municipal Road Congestion Situation in Dust Meteorology

Abstract

The multi-factor warning method for municipal road congestion in sand and dust meteorology belongs to the field of intelligent IoT equipment design and construction technology. Influenced by the law, the technical means of constructing statistics by pre-processing physical quantity monitoring values, generating classified sample sets, and supervised learning, the main steps include building a meteorological-road condition monitoring and early warning system platform, meteorological-road condition data association pre-processing, generating classified sample sets, Step-by-step training prediction model sequence, congestion situation prediction and information release. The measurement method of each physical quantity is feasible, the system architecture meets the requirements of site layout, and the calculation principle and steps are clear, which improves the interpretability of the early warning method for municipal road congestion in sand and dust weather, has strong practicability, and can effectively improve the congestion of municipal roads in sand and dust weather. Reliability of situation warning and effectiveness of information dissemination.

Description

technical field [0001] The invention relates to the technical field of design and construction of intelligent IoT equipment, in particular to a multi-factor early warning method for dust weather municipal road congestion. Background technique [0002] A road traffic dust control measure effect evaluation system and evaluation method (application publication number: CN104237093A, public announcement date: 2014-12-24) uses the dust particle concentration monitoring device to obtain the particle concentration, and proposes the control efficiency based on the dust emission potential calculation formula. [0003] A UAV-based dust monitoring system (application publication number: CN107909790A, public announcement date: 2018.04.13) calculates the dust concentration according to the lambert-beer law by measuring the change of light intensity when it is incident and after it penetrates. [0004] Vehicle dust particle emission factor measurement system and measurement method (applic...

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Problems solved by technology

[0011] In the existing methods, calculated by mie scattering theory and other theoretical methods, there is a large gap between the basic assumptions and the actual environmental factors, and the influence of medium particle movement and human vision persistence is not considered, and the practical application in dusty weather is limited. limitations

There is a lack of a statistical analysis model for pre-processing statistics, and the interpretability of the prediction model is lacking, and the prediction model does not take into account the irregular distribution of wind direction in the urban area, the irregular distribution of sand and dust particle concentration, the sight of vehicles and the direction of sand and dust movement. Irregular distribution leads to the influence of differences in driver's visual perception on different road sections